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Job Description We are seeking candidates for a 3-year PhD project as part of the European Marie Skłodowska-Curie Actions Doctoral Network on “Consumer Energy Demand Flexibility in Electricity Use
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quantum systems and quantum networking theory. Experience with numerical modeling of open photonic quantum systems. Experience with scientific computing using Python and/or Julia. Desired qualifications
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learning approaches and develop a theoretical understanding potentially based on differential geometry. In particular, deep neural networks perform surprisingly well on unseen data, a phenomenon known as
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research facilities and technologies, situated in close connection to the research environment, and a comprehensive national and international research network and good industrial and professional
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, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and
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into the cilia research field and networking. Access to an international collaborative environment that can be used for a mandatory up to 6 months research mobility. Access to state-of-the-art equipment
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software to increase both the accuracy and efficiency of structural digital representation as virtual digital twins, providing high-quality value-added services to the industry. Responsibilities and
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loads — EV fleets, residential batteries, smart heat pumps, and data-center clusters — across distribution and transmission networks is critical to unlocking deep decarbonization and maintaining grid
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. Below, intended research objectives are listed, but the list is not exclusive. We expect the qualified candidate to further define the plan for the PhD within the first three months of employment
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Development/upgrading solid oxide cell test setups for advanced electrochemical characterisation, including development of metal test houses Development of dedicated circuitry and analysis software